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Predictive biomarkers of ossification progression and bone metabolism dynamics in patients with cervical ossification of the posterior longitudinal ligament
Authors:Katsumi  Keiichi  Watanabe  Kei  Yamazaki  Akiyoshi  Hirano  Toru  Ohashi  Masayuki  Mizouchi  Tatsuki  Sato  Masayuki  Sekimoto  Hiroyuki  Izumi  Tomohiro  Shibuya  Yohei  Kawashima  Hiroyuki
Affiliation:1.Spine Center, Department of Orthopedic Surgery, Niigata Central Hospital, 1-18 Shinkocho, Chuo-Ku, Niigata, 950-8556, Japan
;2.Department of Orthopedic Surgery, Niigata University Medical and Dental General Hospital, 1-757 Asahimachidori, Chuo-Ku, Niigata, 951-8510, Japan
;3.Department of Orthopedic Surgery, Uonuma Institute of Community Medicine, Niigata University Medical and Dental Hospital, 4132 Urasa, Minami-Uonuma City, Niigata, 949-7302, Japan
;4.Department of Orthopedic Surgery, Niigata Minami Hospital, 2007-6, Toyano, Chuo-Ku, Niigata, 950-8601, Japan
;5.Department of Orthopedic Surgery, Niigata Prefectural Shibata Hospital, 1-2-8, Honcho, Shibata, Niigata, 957-8588, Japan
;
Abstract:Purpose

This study aimed to establish biomarkers to predict the progression of ossification by examining ossification volume and bone metabolism dynamics in patients with ossification of the posterior longitudinal ligament (OPLL).

Methods

We assessed OPLL progression using computed tomography-based three-dimensional (3D) image analysis and examined bone metabolism dynamics in 107 patients with OPLL (men, 72; women, 35; mean age, 63.6 years). The volume of OPLL was calculated twice during the follow-up period, and OPLL progression was evaluated by the annual rate of ossification increase. Bone metabolism dynamics were assessed by routine blood tests and analysis of various serum biomarkers (including 25-hydroxyvitamin D, intact parathyroid hormone, fibroblast growth factor 23, intact N-terminal propeptide of type 1, tartrate-resistant acid phosphatase isoform 5b, sclerostin, and Dickkopf-1) and bone mineral density (BMD). Patients were classified into the progression (P) or non-progression (NP) group according to the annual rate of increase in previous 3D image analyses, and associated factors between these groups were compared.

Results

The P and NP groups consisted of 29 patients (23 men and 6 women) and 78 patients (49 men and 29 women), respectively. Univariate analysis revealed significant differences in terms of age, body mass index, serum phosphorus, serum sclerostin, and BMD. In multivariate analysis, age, serum phosphorus, and serum sclerostin were identified as independent factors associated with OPLL progression.

Conclusion

Younger age, hypophosphatemia, and high serum sclerostin are risk factors for OPLL progression. Serum phosphorus and sclerostin could serve as important biomarkers for predicting ossification progression.

Keywords:
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